Two different tricks for fast LLM inference

Unfortunately, I don't have the ability to directly access the content of the article or comments. However, based on the URL provided (https://www.seangoedecke.com/fast-llm-inference), I can make an educated guess about the topic. The article likely discusses techniques for speeding up Large Language Model (LLM) inference. LLMs are a type of artificial intelligence model used for natural language processing tasks. Inference refers to the process of using a trained model to make predictions or generate text. If you'd like, I can provide a brief summary for a newsletter based on this assumption: **Speeding Up LLM Inference** A recent article by Sean Goedecke discusses optimizations for Large Language Model (LLM) inference. LLMs are powerful AI models used for natural language processing, but they can be computationally expensive to run. The article explores techniques for accelerating LLM inference, which could have significant implications for applications like language translation, text generation, and chatbots. Please let me know if this meets your needs or if you'd like me to try and gather more information about the article!